{"uid":"cap_HWTQ6wVV9Xppg36SvRaX_","slug":"join-coverage-record-quality-audit-and-adjacent-row-changes-dceae1a7","name":"Join Coverage Record Quality Audit and Adjacent Row Changes","description":"Join coverage — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes for supplied join coverage records (matched_rows, source_rows). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-011?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_8E9RNB5_o-2gPL-6bEyud","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Performs two analytical reports on join coverage data — a record quality audit and adjacent row change detection — for up to 200 supplied rows of matched_rows and source_rows metrics.","exampleAgentPrompt":"Can you run a record quality audit and adjacent row change report on my join coverage data? I have 4 rows for groups 'group-a' and 'group-b' from 2026-10-01 to 2026-10-04, with matched_rows values of 10, 20, 15, 30 and source_rows of 1, 2, 3, 4 — analyze the matched_rows field.","exampleUseCases":[{"title":"ETL pipeline join health check","prompt":"I want to audit the quality of my ETL join results — here are 5 records across dataset groups 'orders' and 'customers' from 2026-09-01 to 2026-09-05 with their matched_rows and source_rows counts. Can you run a record quality audit and check for adjacent row changes on the matched_rows field?"},{"title":"Detecting sudden drops in match rates","prompt":"My join coverage for 'product-catalog' group has been fluctuating — I have 8 daily rows from 2026-08-01 to 2026-08-08 with matched_rows and source_rows. Can you check the source_rows field for adjacent row changes and flag any quality issues?"},{"title":"Multi-group join coverage comparison audit","prompt":"I have 20 join coverage records across three dataset groups — 'transactions', 'users', and 'sessions' — spanning 2026-07-01 to 2026-07-20. Run both the record quality audit and adjacent row changes analysis on the matched_rows field so I can see where coverage is degrading."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying issues such as nulls, out-of-range values, or anomalies in the supplied join coverage rows; and (2) an adjacent row change report highlighting how matched_rows or source_rows values shift between consecutive rows within the dataset. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) rejected","Invalid field enum value (not 'matched_rows' or 'source_rows') causes error","Empty rows array (minItems: 1 not met) rejected"],"whenToPreferThis":"Choose this endpoint when you need a quick, offline analytical double-report on join coverage metrics — specifically when you want both a record quality audit and adjacent row change detection in a single $0.01 call for up to 200 rows. It is ideal for data engineers and pipeline monitors who already have join coverage data (matched_rows, source_rows) and need structured quality and change analysis without any external data enrichment, predictions, or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:47.535Z","isFirstParty":false,"canonicalSlug":"join-coverage-record-quality-audit-and-adjacent-row-changes-dceae1a7"}